arXiv research

The paper studies geodesics on a specific group using sub-Finsler norms.

Researchers solved Minkowski's quadratic inequality extremals.

Paper proposes a method to identify wind hazard types and predict extreme wind speeds.

Study on pairwise counter-monotonicity, a type of negative dependence.

Many scientific and engineering challenges -- ranging from pharmacokinetic drug dosage allocation and personalized medicine to marketing mix (4Ps) recommendations -- require an understanding of the unobserved heterogeneity in order to develop the best decision making-processes. In this paper, we develop a hypothesis te…

Study free energy in spherical spin glasses, proving universality dichotomy.

Bayesian econometrics improves nowcasting during pandemics.

Classifies states of four rebits using group theory.

AF improves classification models by adaptively weighting trees.

The paper explores the relationship between joint mixability and negative dependence structures.

We generalize the Riesz potential of a compact domain in $\mathbb{R}^{m}$ by introducing a renormalization of the $r^{α-m}$-potential for $α\le0$. This can be considered as generalization of the dual mixed volumes of convex bodies as introduced by Lutwak. We then study the points where the extreme values of the (renorm…

Markov chain Monte Carlo (MCMC) algorithms are simple and extremely powerful techniques to sample from almost arbitrary distributions. The flaw in practice is that it can take a large and/or unknown amount of time to converge to the stationary distribution. This paper gives sufficient conditions to guarantee that univa…

The paper develops mixed-integer formulations for neural networks using partitioning.

DMIDAS improves long-term forecasting accuracy in healthcare and electricity data.

Generalizes pseudo-product structures with abnormal extremals.

A new quantization strategy reduces Transformer model size and inference time.

Deep neural networks improve ensemble weather forecasts.

The claim experience of the past is a very important information to calculate the fair price of an insurance contract. In a lot of European countries for instance the prices for motor car insurance depend on the number of claims the driver has reported to the insurance company during the last years. Classically these p…

The paper constructs free boundary minimal surfaces in product spaces using eigenvalue methods.

The majority of real-world networks are dynamic and extremely large (e.g., Internet Traffic, Twitter, Facebook, ...). To understand the structural behavior of nodes in these large dynamic networks, it may be necessary to model the dynamics of behavioral roles representing the main connectivity patterns over time. In th…

Sample measures of top centile contributions to the total (concentration) are downward biased, unstable estimators, extremely sensitive to sample size and concave in accounting for large deviations. It makes them particularly unfit in domains with power law tails, especially for low values of the exponent. These estima…

Optimizes risk assessment tools using mixed-integer programming.

In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and typically attains an order of magnitude or better improvement in optimization pe…

We investigate the relationship between stability and the existence of extremal Kähler metrics on certain toric surfaces. In particular, we consider how log stability depends on weights for toric surfaces whose moment polytope is a quadrilateral. We introduce a space of symplectic potentials for toric manifolds, which …

We propose a novel parameterized family of Mixed Membership Mallows Models (M4) to account for variability in pairwise comparisons generated by a heterogeneous population of noisy and inconsistent users. M4 models individual preferences as a user-specific probabilistic mixture of shared latent Mallows components. Our k…

Novel IMEX scheme solves financial PDEs with mixed derivatives.

Develops a bi-variate stochastic framework to model mortality and interest rates with long-range dependence.

We study a model of wealth dynamics [Bouchaud and Mézard 2000, \emph{Physica A} \textbf{282}, 536] which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a ful…

MixBoost generates synthetic instances to balance imbalanced datasets.

New method estimates sparse covariance matrices in logit mixtures.

Split-Merge MCMC (Monte Carlo Markov Chain) is one of the essential and popular variants of MCMC for problems when an MCMC state consists of an unknown number of components. It is well known that state-of-the-art methods for split-merge MCMC do not scale well. Strategies for rapid mixing requires smart and informative …

Classifier evasion consists in finding for a given instance $x$ the nearest instance $x'$ such that the classifier predictions of $x$ and $x'$ are different. We present two novel algorithms for systematically computing evasions for tree ensembles such as boosted trees and random forests. Our first algorithm uses a Mixe…

A neural network method improves CVA computations for complex financial portfolios.

In this paper we deal with two classes of mixed metric 3-structures, namely the mixed 3-Sasakian structures and the mixed metric 3-contact structures. Firstly we study some properties of the curvature of mixed 3-Sasakian structures, proving that any manifold endowed with such a structure is Einstein. Then we prove the …

Mixed-SCORE+ improves community detection in weak signal networks.

The paper explores knotoids, pseudo knotoids, braidoids, and pseudo braidoids on the torus.

New method for mixed memberships using symmetrized Laplacian inverse matrix.

NPMLE estimator automatically chooses the right model complexity for Gaussian mixtures.

Society's drive toward ever faster socio-technical systems, means that there is an urgent need to understand the threat from 'black swan' extreme events that might emerge. On 6 May 2010, it took just five minutes for a spontaneous mix of human and machine interactions in the global trading cyberspace to generate an unp…

This study examines whether PCA can effectively identify nitrogen pollution sources in rivers.

We present a method to generate renewable scenarios using Bayesian probabilities by implementing the Bayesian generative adversarial network~(Bayesian GAN), which is a variant of generative adversarial networks based on two interconnected deep neural networks. By using a Bayesian formulation, generators can be construc…

GPU optimization speeds up large-scale classification tasks.

Synchronized stochastic gradient descent (SGD) optimizers with data parallelism are widely used in training large-scale deep neural networks. Although using larger mini-batch sizes can improve the system scalability by reducing the communication-to-computation ratio, it may hurt the generalization ability of the models…

New mixed-platonic 3-manifolds from different polyhedra types.

The literature on statistical learning for time series assumes the asymptotic independence or ``mixing' of the data-generating process. These mixing assumptions are never tested, nor are there methods for estimating mixing rates from data. We give an estimator for the $β$-mixing rate based on a single stationary sample…

Unified Minkowski problem discussed for (p,q)-mixed quermassintegrals.

Mix-IRLS solves imbalanced mixed linear regression problems efficiently.

Mixed 3-structures are odd-dimensional analogues of paraquaternionic structures. They appear naturally on lightlike hypersurfaces of almost paraquaternionic hermitian manifolds. We study invariant and anti-invariant submanifolds in a manifold endowed with a mixed 3-structure and a compatible (semi-Riemannian) metric. P…